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NIPS
2001
13 years 10 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
TFS
2008
230views more  TFS 2008»
13 years 8 months ago
SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
Abstract--This paper considers the automatic design of fuzzyrule-based classification systems from labeled data. The performance of classifiers and the interpretability of generate...
Eghbal G. Mansoori, Mansoor J. Zolghadri, Seraj D....
IPSN
2005
Springer
14 years 2 months ago
Avrora: scalable sensor network simulation with precise timing
— Simulation can be an important step in the development of software for wireless sensor networks and has been the subject of intense research in the past decade. While most prev...
Ben Titzer, Daniel K. Lee, Jens Palsberg
OOPSLA
2005
Springer
14 years 2 months ago
CodeQuest: querying source code with datalog
We describe CodeQuest, a system for querying source code. It combines two previous proposals, namely the use of logic programming and database system. Experiments (on projects ran...
Elnar Hajiyev, Mathieu Verbaere, Oege de Moor, Kri...
FSTTCS
2006
Springer
14 years 18 days ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys